Elasticsearch is a distributed, RESTful search and analytics engine capable of solving a growing number of use cases. As the heart of the Elastic Stack, it centrally stores your data so you can discover the expected and uncover the unexpected. 
 
 Its feature include: 
 <ul>
	<li>Distributed and Highly Available Search Engine.
	<ul>
		<li>Each index is fully sharded with a configurable number of shards.</li>
		<li>Each shard can have one or more replicas.</li>
		<li>Read / Search operations performed on either one of the replica shard.</li>
	</ul></li>
	<li>Multi Tenant with Multi Types.
	<ul>
		<li>Support for more than one index.</li>
		<li>Support for more than one type per index.</li>
		<li>Index level configuration (number of shards, index storage, &#8230;).</li>
	</ul></li>
	<li>Various set of APIs
	<ul>
		<li>HTTP RESTful API</li>
		<li>Native Java API.</li>
		<li>All APIs perform automatic node operation rerouting.</li>
	</ul></li>
	<li>Document oriented
	<ul>
		<li>No need for upfront schema definition.</li>
		<li>Schema can be defined per type for customization of the indexing process.</li>
	</ul></li>
	<li>Reliable, Asynchronous Write Behind for long term persistency.</li>
	<li>(Near) Real Time Search.</li>
	<li>Built on top of Lucene
	<ul>
		<li>Each shard is a fully functional Lucene index</li>
		<li>All the power of Lucene easily exposed through simple configuration / plugins.</li>
	</ul></li>
	<li>Per operation consistency
	<ul>
		<li>Single document level operations are atomic, consistent, isolated and durable.</li>
	</ul></li>
</ul>

Elasticsearch is a distributed, RESTful search and analytics engine capable of solving a growing number of use cases. As the heart of the Elastic Stack, it centrally stores your data so you can discover the expected and uncover the unexpected. 

ElasticSearch - Distributed, RESTful search and analytics engine

Solr is the popular, blazing fast open source enterprise search platform from the Apache Lucene project. Its major features include powerful full-text search, hit highlighting, faceted search, dynamic clustering, database integration, and rich document (e.g., Word, PDF) handling. Solr is highly scalable, providing distributed search and index replication, and it powers the search and navigation features of many of the world's largest internet sites. Solr is written in Java and runs as a standalone full-text search server within a servlet container such as Tomcat. Solr uses the Lucene Java search library at its core for full-text indexing and search, and has REST-like HTTP/XML and JSON APIs that make it easy to use from virtually any programming language. Solr's powerful external configuration allows it to be tailored to almost any type of application without Java coding, and it has an extensive plugin architecture when more advanced customization is required. Its feature set include Rich Document Parsing and Indexing (PDF, Word, HTML, etc) using Apache Tika, An Administration Interface, Monitorable Logging, Fast Incremental Updates and Index Replication, Highly Scalable Distributed search with sharded index across multiple hosts, HTTP interface with configurable response formats (XML/XSLT, JSON, Python, Ruby, PHP, Velocity) Solrj is embedded solr. It provides Java based API and it takes care of constructing, parsing, sending and receiving HTTP request.

Solr is the popular, blazing fast open source enterprise search platform from the Apache Lucene project. Its major features include powerful full-text search, hit highlighting, faceted search, dynamic clustering, database integration, and rich document (e.g., Word, PDF) handling. Solr is highly scalable, providing distributed search and index replication, and it powers the search and navigation features of many of the world's largest internet sites. 

Solr - Blazing-fast, open source enterprise search platform

IndexTank search engine powers search in Reddit, Social bookmarking site. IndexTank is acquired by LinkedIn and released the project as open source. It includes features like Variables boosts, Facets, Faceted search, Snippeting, Custom scoring functions, Suggest, and Autocomplete. 
 Homepage: <A HREF="http://indextank.com/" target="_blank">http://indextank.com/</A>

IndexTank search engine powers search in Reddit, Social bookmarking site. IndexTank is acquired by LinkedIn and released the project as open source. It includes features like Variables boosts, Facets, Faceted search, Snippeting, Custom scoring functions, Suggest, and Autocomplete.

IndexTank - Search Engine powers Reddit

Lucene is most popular and java based searchengine library. It offers near real time search. Its features include Ranked search, many powerful query types: phrase queries, wildcard queries, proximity queries, range queries and more, fielded searching (e.g., title, author, contents), date-range searching, sorting by any field , multiple-index searching with merged results , allows simultaneous update and searching. 

Apache Lucene is a high-performance, full-featured text search engine library written entirely in Java. It is a technology suitable for nearly any application that requires full-text search, especially cross-platform.

Lucene - A high-performance, full-featured text search engine library

OpenSearch is a community-driven, open source search and analytics suite derived from Apache 2.0 licensed Elasticsearch 7.10.2 & Kibana 7.10.2. It consists of a search engine daemon, OpenSearch, and a visualization and user interface, OpenSearch Dashboards. OpenSearch enables people to easily ingest, secure, search, aggregate, view, and analyze data. These capabilities are popular for use cases such as application search, log analytics, and more.
 
Its features include: 
<ul><li>Log analytics</li><li> Real-time application monitoring</li><li> Clickstream analytics</li><li>Use SQL or a piped processing language to query your data</li><li>Automate index operations</li><li>Monitor and optimize your cluster</li><li>Run search requests in the background</li><li>KNN- Find “nearest neighbors” in your vector data</li><li>Authentication and access control for your cluster</li><li>Anomaly Detection</li></ul>

OpenSearch is a community-driven, open source search and analytics suite derived from Apache 2.0 licensed Elasticsearch 7.10.2 & Kibana 7.10.2. It consists of a search engine daemon, OpenSearch, and a visualization and user interface, OpenSearch Dashboards. OpenSearch enables people to easily ingest, secure, search, aggregate, view, and analyze data. These capabilities are popular for use cases such as application search, log analytics, and more.

OpenSearch - Open source distributed and RESTful search engine

Lunr.js is a small, full-text search library for use in the browser. It indexes JSON documents and provides a simple search interface for retrieving documents that best match text queries. A bit like Solr, but much smaller and not as bright. Lunr enables you to provide a great search experience without the need for external, server-side, search services. Lunr has no external dependencies and works in your browser or on the server with node.js.
 
For web applications with all their data already sitting in the client, it makes sense to be able to search that data on the client too. A local search index will be quicker, there is no network overhead, and will remain available and usable even without a network connection.

Lunr.js is a small, full-text search library for use in the browser. It indexes JSON documents and provides a simple search interface for retrieving documents that best match text queries. A bit like Solr, but much smaller and not as bright. Lunr enables you to provide a great search experience without the need for external, server-side, search services. Lunr has no external dependencies and works in your browser or on the server with node.js.

LUNR.js - A bit like Solr, but much smaller and not as bright

An open source .NET web crawler written in C# using SQL 2005/2008. Arachnode.net is a complete and comprehensive .NET web crawler for downloading, indexing and storing Internet content including e-mail addresses, files, hyperlinks, images, and Web pages. Its features include
 <UL>
	<LI>.NET architecture</LI>
	<LI>Configurable Rules and Actions</LI>
	<LI>Lucene.NET Integration</LI>
	<LI>SQL Server 2008 and full-text indexing</LI>
	<LI>.DOC/.PDF/.PPT/.XLS Indexing</LI>
	<LI>HTML to XML and XHTML</LI>
	<LI>Multi-threading and Throttling</LI>
	<LI>Respectful Crawling</LI>
	<LI>Analysis Services</LI>
	<LI>SQL Server 2008 and SSIS</LI>
	<LI>EXIF data extraction</LI>
 </UL>

An open source .NET web crawler written in C# using SQL 2005/2008. Arachnode.net is a complete and comprehensive .NET web crawler for downloading, indexing and storing Internet content including e-mail addresses, files, hyperlinks, images, and Web pages.

Arachnode.net

Open Search Server is both a modern crawler and search engine and a suite of high-powered full text search algorithms. Built using the best open source technologies like lucene, zkoss, tomcat, poi, tagsoup. Open Search Server is a stable, high-performance piece of software.
 <UL>
	<LI>Multi-languages indexing</LI>
	<LI>The crawlers go through web sites and file systems to rapidly and easily build your index.</LI>
	<LI>Numerous document formats are supported, such as XML, HTML/XHTML, Adobe™ PDF, Microsoft™ Word™, PowerPoint™, OpenOffice™, etc</LI>
	<LI>Quick integration thanks to an XML interface via HTTP queries (XML over HTTP) and PHP classes</LI>
	<LI>The web interface is built around the power offered by the Zkoss framework. It runs with the main Ajax browsers. This RIA-type interface is as comfortable to use as that of a heavy client</LI>
 </UL>

Open Search Server is both a modern crawler and search engine and a suite of high-powered full text search algorithms. Built using the best open source technologies like lucene, zkoss, tomcat, poi, tagsoup. Open Search Server is a stable, high-performance piece of software.

Open Search Server

Grub Next Generation is distributed web crawling system (clients/servers) which helps to build and maintain index of the Web. It is client-server architecture where client crawls the web and updates the server. The peer-to-peer grubclient software crawls during computer idle time.

Grub

CLucene is a port of the very popular Java Lucene text search engine API. CLucene aims to be a good alternative to Java Lucene when performance really matters or if you want to stick to good old C++. CLucene is faster than Lucene as it is written in C++, meaning it is being compiled into machine code, has no background GC operations, and requires no any extra setup procedures.

CLucene - Lucene C Port

Constellio Open Source Enterprise Search is based on Apache Solr and using Google Search Appliances connectors architecture, it allows, with a single click, to find all relevant content in your organization (Web, email, ECM, CRM etc.). 

 It supports Federated search, Using the single interface data in the organization could be discovered or searched. It provides multi-lingual search. Support for more than 15 languages are available. It has support of automatic document classification, adding tags or keywords to the documents. Additional to that this product has all kind of feature a Enterprise Search engine should have. It supports reporting on indexing and search, Sort results, Synonyms search, Thesaurus support, Auto complete, Facet etc. Constellio can index SharePoint sites, Documentum, FileNet, LiveLink. 

 Google's Enterprise Connector Manager provides support to retrieve data from different sources like database, file system, CRM, Email etc. Data from database could be retrieved using <A HREF="http://code.google.com/p/google-enterprise-connector-database/" target="_blank">Database connector</A>. This product most efficiently using this and retrieves the data from different sources. It uses Apache Solr to index the content. 

 Constellio's secure web interface will allow you to search your email and access attached files. It also provides API support in Ruby, PHP, Java, Python, JSon, C#, ColdFusion. Google's Enterprise Connector used in Google Search Appliance is constantly adding more connectors to retrieve data from different sources. Since Constellio uses this more Enterprise search support will be provided.

Constellio Open Source Enterprise Search is based on Apache Solr and using Google Search Appliances connectors architecture, it allows, with a single click, to find all relevant content in your organization (Web, email, ECM, CRM etc.).

Constellio - Enterprise Search engine

Whoosh is a fast, featureful full-text indexing and searching library implemented in pure Python. Programmers can use it to easily add search functionality to their applications and websites. It has support of Fielded indexing, search, scoring, text analysis, storage, Pluggable scoring algorithm, Powerful query language and spell-checker.

Whoosh - Python Search Library

Typesense is an open source, typo tolerant search engine that is optimized for instant sub-50ms searches, while providing an intuitive developer experience. 
 
Features: 
<ul>
<li>Typo Tolerance: Handles typographical errors elegantly, out-of-the-box.</li>
<li>Simple and Delightful: Simple to set-up, integrate with, operate and scale.</li>
<li>Blazing Fast: Built in C++. Meticulously architected from the ground-up for low-latency (&lt;50ms) instant searches.</li>
<li>Tunable Ranking: Easy to tailor your search results to perfection.</li>
<li>Sorting: Sort results based on a particular field at query time (helpful for features like "Sort by Price (asc)").</li>
<li>Faceting &amp; Filtering: Drill down and refine results.</li>
<li>Grouping &amp; Distinct: Group similar results together to show more variety.</li>
<li>Federated Search: Search across multiple collections (indices) in a single HTTP request.</li>
<li>Scoped API Keys: Generate API keys that only allow access to certain records, for multi-tenant applications.</li>
<li>Synonyms: Define words as equivalents of each other, so searching for a word will also return results for the synonyms defined.</li>
<li>Curation &amp; Merchandizing: Boost particular records to a fixed position in the search results, to feature them.</li>
<li>Raft-based Clustering: Setup a distributed cluster that is highly available.</li>
<li>Seamless Version Upgrades: As new versions of Typesense come out, upgrading is as simple as swapping out the binary and restarting Typesense.</li>
</ul>

Typesense is an open source, typo tolerant search engine that is optimized for instant sub-50ms searches, while providing an intuitive developer experience. 

Typesense - Fast, typo tolerant search engine for building delightful search experiences

Quickwit is a distributed search engine built from the ground up to offer cost-efficiency and high reliability. By mere mortals for mere mortals, Quickwit's architecture is as simple as possible. Quickwit is written in Rust and built on top of the mighty tantivy library. It designed to index big datasets straight from object storage like AWS S3 in a stateless manner. 
<ul>
<li>Scalable distributed search: Host an arbitrary number of indexes on Amazon S3 and answer search queries in less than a second with a small pool of stateless search instances</li>
<li>Stream indexing: Ingest TB of data from your favorite distributed event streaming service. As of today, Quickwit supports Apache Kafka natively. The next releases will bring support for more platforms</li>
<li>Fault-tolerant architecture that won't lose data: Quickwit achieves exactly-once processing for indexing and safely stores your data on highly reliable object storage services such as Amazon S3</li>
<li>Cloud-native, easy to operate: Thanks to true decoupled compute and storage, search instances are stateless, add or remove search nodes within seconds</li>
<li>Sub-second full-text search on cloud / distributed storage: Quickwit Search re-designed indexing and index data structure to open it in less than 60ms on Amazon S3</li>
<li>Time-based sharding: Quickwit shards data by time when enabled. And you can use a second dimension to shard data thanks to our <a href="../../docs/design/querying">tags feature</a>. Time-based queries only access splits (a data piece of the index) that match the time range of the query which leads to significant performance improvements</li>
<li>Painless multi-tenant search: Create indexes for each tenant without hurting query performance. Or group tenants into one index and use tagging to prune irrelevant splits for your tenant query to improve significantly performance</li>
<li>Elasticsearch query language support</li>
<li>Decoupled compute and storage, stateless indexers &amp; searchers</li>
<li>Schemaless analytics</li>
</ul>

Quickwit is a distributed search engine built from the ground up to offer cost-efficiency and high reliability. By mere mortals for mere mortals, Quickwit's architecture is as simple as possible. Quickwit is written in Rust and built on top of the mighty tantivy library. It designed to index big datasets straight from object storage like AWS S3 in a stateless manner.

Quickwit - Fast and cost-efficient distributed search engine for immutable data

Jumper 2.0 is a collaborative community search platform that revolutionizes search by crowdsourcing knowledge management powered by a shared bookmarking engine. It is easily and quickly deployed into a community of practice that benefits users with complex and specialized search requirements. Jumper delivers universal search of any databases, flat files, fileshares, content systems, web pages, blogs and wikis, even people - through one simple search box. Jumper 2.0 collaborative search is an open source, web-based platform written in PHP and Javascript. Jumper uses peer and social-networking principles to tag and link distributed information resources to create an interactive, user-submitted, recommendation engine that allows you to search any content, media, or data regardless of format or location. Like Wikipedia, Jumper allows users to become contributors and editors of the service by creating, editing, and managing tag profiles. Jumper allows users to tag any information resource with keywords just like Delicious. Jumper delivers a comment and rating system that is similar to Amazon.

Jumper 2.0 is a collaborative community search platform that revolutionizes search by crowdsourcing knowledge management powered by a shared bookmarking engine. It is easily and quickly deployed into a community of practice that benefits users with complex and specialized search requirements. Jumper delivers universal search of any databases, flat files, fileshares, content systems, web pages, blogs and wikis, even people - through one simple search box.

Jumper - Collaborative search engine in PHP

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